Paris Dauphine University

About: Paris Dauphine University is a education organization based out in Paris, France. It is known for research contribution in the topics: Context (language use) & Population. The organization has 1766 authors who have published 6909 publications receiving 162747 citations. The organization is also known as: Paris Dauphine & Dauphine.

Cost of illness and disease severity in a cohort of French patients with Parkinson's disease.

Abstract: Objective: To assess the relationship between severity and progression of illness in Parkinson’s disease and the use of healthcare resources. Design and setting: This was a prospective cost-of-illness study conducted in France based on clinical observation over a 6-month period of patients with Parkinson’s disease treated in the hospital or community setting. Regression analyses were performed to construct the model that offered the best explanation for health expenditures using clinical and sociodemographic indicators. Patients and participants: All patients included in the study had well-defined idiopathic Parkinson’s disease, were aged >35 years, were receiving treatment with levodopa or other antiparkinsonian agents, and were capable of completing questionnaires, alone or with the help of a household member. The final study population consisted of 294 patients, of whom 54 were enrolled by general practitioners and 240 by neurologists. Interventions: Investigators completed a clinical questionnaire at the beginning and end of the 6-month observation period. Patients completed a questionnaire on their daily living conditions at the beginning and end of the study, and also completed monthly reports of healthcare use and loss of productivity. Patients with motor fluctuations also filled in fluctuation diaries on 4 consecutive days at the beginning and end of the 6-month period. Resource data collected included hospital stays, ancillary care, drug therapy, medical visits and transportation. Social costs were evaluated in nonmonetary terms, with the exception of costs of adapting the home environment. Transfer payments were analysed using reports from patients. Main outcome measures and results: Hospital stays were the most expensive component of care (39% of costs), followed by ancillary care (30%) and drug therapy (22%). The mean medical cost was 308 euros (EUR) [$US357] for patients followed by a general practitioner and EUR2580 ($US2993) for patients followed by a neurologist. Costs also varied with age and motor fluctuations. Medical costs were strongly correlated with most clinical indicators and the cost generally progressed in line with the severity of the disease. The strongest correlation was between clinical indicators and ancillary care costs. Conclusions: These results confirm the importance of the social burden of Parkinson’s disease. The regression results could be used to evaluate the benefit of novel treatments that reduce the intensity of motor fluctuations.

A general elicitation-free protocol for allocating indivisible goods

Abstract: We consider the following sequential allocation process. A benevolent central authority has to allocate a set of indivisible goods to a set of agents whose preferences it is totally ignorant of. We consider the process of allocating objects one after the other by designating an agent and asking her to pick one of the objects among those that remain. The problem consists in choosing the "best" sequence of agents, according to some optimality criterion. We assume that agents have additive preferences over objects. The choice of an optimality criterion depends on three parameters: how utilities of objects are related to their ranking in an agent's preference relation; how the preferences of different agents are correlated; and how social welfare is defined from the agents' utilities. We address the computation of a sequence maximizing expected social welfare under several assumptions. We also address strategical issues.

Learning in mean field games: The fictitious play

Abstract: Mean Field Game systems describe equilibrium configurations in differential games with infinitely many infinitesimal interacting agents. We introduce a learning procedure (similar to the Fictitious Play) for these games and show its convergence when the Mean Field Game is potential.